DHU Radar

Machine Learning for Clinical Management – efficiency and better care

Keywords: Chronic Diseases, Data Analysis, Quality of Care, Resources, Risk Stratification
Amalfi Analytics
Digital solution and service (e.g. application/digital health portal/platform/AI based system/etc.)
Short description
We have created a platform to help making better management decisions in healthcare systems. Using data that healthcare organizations already have, we provide decision makers with views of the real need of their population, anticipate activity that has to be covered, and estimate availability and costs of the necessary resources. We cover all levels of healhcare systems: hospital departments, hospitals as a whole, primary care, territorial planning and even socio-sanitary care. For hospitals we have modules that anticipate influx to emergency departments, needs for beds (hospitalization) and surgical areas, and unprogrammed absenteeism among professinals. For all levels we provide a way to investigate variability within a pathology, to identify patient patterns with specific risks, needs, or personalized protocols. The platform is provided in SaaS mode; It feeds on routine/administrative data that all organizations have, and using Machine Learning algorithms creates predictive or descriptive models adapted to that organization (e.g. hospital). Unlike many AI-in-healthcare solutions, deployment is painless and quick, and the learning curve very low. There is a one-time setup fee and then a subscription fee payable monthly or yearly (whose amount depends on various factors, including organization size).
Impact on health outcomes, Economic value to health and care systems, Impact on the health system’s capacity and resilience (e.g., health and care efficiency, continuity of care)
The practice/case/tool is “on the market” and integrated in routine use. There is proven market impact in terms of job creation/spin-off creation or other company growth
Geographical scope
It could be deployed in any European Practice
English, Spanish, French, Catalan
10 sites, aiming at 30 by the end of 2023 and 200 by the end of 2024.
Submitted in other database or repository of digital health resources that is publicly available

Additional information

to clinicians / care practitioners
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
Care pathway tracking and adherence
Regional and national Electronic Health Record systems
to patients / citizens
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
Home care
Primary target patient group (age)
May be used across all patient ages
Use case and care pathway positioning
Integrated care pathways, Reuse of data for research
Ready to be transferred to
Ready for transfer, but the practice has not been transferred yet.
Plans for cross-border implementation
Are considered and will be developed in the near future